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IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： Alberto Mulone Sherine Awad Davide Chiarugi Marco Aldinucci Department of Computer Science University of Turin Turin Italy Institute of Metabolic Science University of Cambridge Cambridge United Kingdom Research and Development Group - Computing and Databases Services Max Planck Institute for Human Cognitive and Brain Science Leipzig Germany

In recent years we have understood the importance of analyzing and sequencing human genetic variation. A relevant aspect that emerged from the Covid-19 pandemic was the need to obtain results very quickly; this involved using High-Performance computing (HPC) environments to execute the Next Generation Sequencing (NGS) pipeline. However, HPC is not always the most suitable environment for the entire execution of a pipeline, especially when it involves many heterogeneous tools. The ability to execute parts of the pipeline on different environments can lead to higher performance but also cheaper executions. This work shows the design and optimization process that led us to a state-of-the-art Variant Calling hybrid workflow based on the StreamFlow Workflow Management System (WfMS). We also compare StreamFlow with Snakemake, an established WfMS targeting HPC facilities, observing comparable performance on single environments and satisfactory improvements with a hybrid cloud-HPC configuration.

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Evaluation of Cross-Lingual Bug Localization: Two Industrial Cases

Evaluation of Cross-Lingual Bug Localization: Two Industrial...

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International Conference on Software Maintenance (ICSM)

作者： Shinpei Hayashi Takashi Kobayashi Tadahisa Kato School of Computing Tokyo Institute of Technology Tokyo Japan Research & Development Group Center for Digital Services Hitachi Ltd. Kanagawa Japan

This study reports the results of applying the cross-lingual bug localization approach proposed by Xia et al. to industrial software projects. To realize cross-lingual bug localization, we applied machine translation to non-English descriptions in the source code and bug reports, unifying them into English-based texts, to which an existing English-based bug localization technique was applied. In addition, a prototype tool based on BugLocator was implemented and applied to two Japanese industrial projects, which resulted in a slightly different performance from that of Xia et al.

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Evaluation of Cross-Lingual Bug Localization: Two Industrial Cases

arXiv

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arXiv 2023年

作者： Hayashi, Shinpei Kobayashi, Takashi Kato, Tadahisa School of Computing Tokyo Institute of Technology Tokyo152–8550 Japan Research & Development Group Center for Digital Services Hitachi Ltd. Kanagawa244–0817 Japan

关键词： Machine translation

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Defining an Architecture for a Remote Monitoring Platform to Support the Self-management of Vascular Diseases

Defining an Architecture for a Remote Monitoring Platform to...

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International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2021

作者： Vieira, Ana Carneiro, João Conceição, Luís Martins, Constantino Souza, Julio Freitas, Alberto Marreiros, Goreti GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Institute of Engineering Polytechnic of Porto Porto Portugal CINTESIS – Center for Health Technology and Services Research Porto Portugal

ISBN: (纸本)9783030857097

The aging of the worldwide population has led to a growing prevalence of vascular diseases, negatively impacting national healthcare systems and patients. The application of information technologies in the health sector has the potential to allow the remote monitoring of patients and the personalization of healthcare. This work proposes the architecture for a remote monitoring platform that supports the self-management of vascular diseases in the context of the Inno4Health project, with the goal of stimulating the innovation in the continuous monitoring of the patients’ health. The platform aims to support health professionals and patients with vascular diseases through the continuous monitoring of their health condition and presentation of monitoring reports. Self-management tools will be provided to patients through the presentation of personalized recommendations adapted to their current health condition. By doing so, we believe it will be possible to improve the patients’ self-management of their disease as well as decrease the risk of disease-related complications. © 2021, Springer Nature Switzerland AG.

关键词： Remote control

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Improving the lifestyle behavior of type 2 diabetes mellitus patients using a mobile application

Improving the lifestyle behavior of type 2 diabetes mellitus...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Andreia Pinto João Viana Diogo Martinho Vítor Crista José Miguel Diniz Joana Reis João Matos David Greer Goreti Marreiros Alberto Freitas Department of Community Medicine Information and Health Decision Sciences (MEDCIDS) Faculty of Medicine Center for Health Technology and Services Research (CINTESIS) University of Porto Porto Portugal Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD) Institute of Engineering Polytechnic of Porto Porto Portugal Health Data Science PhD Program Faculty of Medicine Center for Health Technology and Services Research (CINTESIS) University of Porto Lisboa Portugal CLOO - Behavioral Insights Unit Faculty of Psychology CICPSI - Research Center for Psychological Science University of Lisbon Lisboa Portugal Behavioral Insights Unit CLOO Porto Portugal Behavioral Insights Unit CLOO Lisboa Portugal

ISBN: (数字)9781665497923

ISBN: (纸本)9781665497930

Type 2 diabetes is an increasingly prevalent disease and patients do not always manage the disease properly. Therefore, creating tools that help diabetics self-manage their condition over time is of the utmost importance. Technological tools that include features meeting this population's needs, with an integrated personalized feedback system, in an environment of gamified incentives, may be the way for developing a sustained app's usage. This work aims to present a still in development, novel approach to managing diabetes type 2 with a focus on data analysis from user-inputs, gamification, and personalized coaching, with an accessible user interface. Thus, we will present some functionalities, in particular the theoretical and practical concept that is behind this development, namely the Transtheoretical model of behavior change to create different profiles, to provide customized feedback according to the user's behavioral stage, and also to ascertain if it induces any improvement at the behavioral level.

关键词： Computers Data analysis Computational modeling User interfaces Diabetes Behavioral sciences Mobile applications

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AIRDOC: Smart mobile application for individualized support and monitoring of respiratory function and sounds of patients with chronic obstructive disease 12

AIRDOC: Smart mobile application for individualized support ...

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12th IADIS International Conference e-Health 2020, EH 2020, Part of the 14th Multi Conference on Computer Science and Information Systems, MCCSIS 2020

作者： Almeida, Rute Jácome, Cristina Martinho, Diogo Vieira-Marques, Pedro Jacinto, Tiago Ferreira, Ana Almeida, Ana Martins, Constantino Pereira, Mariana Pereira, Ana Valente, José Almeida, Rafael Vieira, Ana Amaral, Rita Sá-Sousa, Ana Gonçalves, Ivânia Rodrigues, Pedro Alves-Correia, Magna Freitas, Alberto Marreiros, Goreti Fonseca, Susana Caldas Pereira, Altamiro Costa Fonseca, João Almeida CINTESIS Center for Health Technology and Services Research Faculty of Medicine University of Porto Porto Portugal MEDCIDS Department of Community Medicine Health Information and Decision Faculty of Medicine University of Porto Porto Portugal GECAD Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Institute of Engineering Polytechnic of Porto Portugal MEDIDA Serviços em Medicina EDucação Investigação Desenvolvimento e Avaliação LDA Porto Portugal Porto Health School Polytechnic Institute of Porto Porto Portugal

ISBN: (纸本)9789898704184

Current tools for self-management of chronic obstructive respiratory diseases (CORD) are difficult to use, not individualized and requiring laborious analysis by health professionals, discouraging their use in healthcare. There is an opportunity for cost-effective and easy-to-disseminate advanced technological solutions directed to patients and attractive to different stakeholders. The strategy of AIRDOC is to develop and integrate self-monitoring and self-managing tools, making use of the smartphone's presence in everyday life. AIRDOC intends to innovate on: i) technologies for remote monitoring of respiratory function and computerized lung auscultation;ii) coaching solutions, integrating psychoeducation, gamification and disease management support systems;and iii) management of personal health data, focusing on security, privacy and interoperability. It is expected that AIRDOC results will contribute for the innovation in CORD healthcare, with increased patient involvement and empowerment while providing quality prospective information for better clinical decisions, allowing more efficient and sustainable healthcare delivery. © Proceedings of the 12th IADIS International Conference e-Health 2020, EH 2020 - Part of the 14th Multi Conference on Computer Science and Information Systems, MCCSIS 2020. All rights reserved.

关键词： mHealth

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Deep transfer learning via minimum enclosing balls 25th

Deep transfer learning via minimum enclosing balls

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25th International Conference on Neural Information Processing, ICONIP 2018

作者： Deng, Zhilong Liu, Fan Zhao, Jiangjiang Wei, Qiang Pang, Shaoning Leng, Yue Algorithm Group Research and Development Department Online Services of China Mobile Beijing China Artificial Intelligence Lab Meituan-Dianping Group Beijing China Department of Computing Unitec Institute of Technology Private Bag 92025 Auckland1142 New Zealand Algorithm Group Artificial Intelligence Lab Emotibot Technologies Limited Beijing China

ISBN: (纸本)9783030041816

Training of deep learning algorithms such as CNN, LSTM, or GRU often requires large amount of data. However in real world applications, the amount of data especially labelled data is limited. To address this challenge, we study Deep Transfer Learning (DTL) in the context of Multitasking Learning (MTL) to extract sharable knowledge from tasks and use it for related tasks. In this paper, we use Minimum Closed Ball (MEB) as a flexible knowledge representation method to map shared domain knowledge from primary task to secondary task in multitasking learning. The experiments provide both analytic and empirical results to show the effectiveness and robustness of the proposed MEB-based deep transfer learning. © Springer Nature Switzerland AG 2018.

关键词： Learning algorithms

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Characterising acute and chronic care needs: insights from the Global Burden of Disease Study 2019

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Nature communications 2025年第1期16卷 4235-4235页

作者： Cecilia Anza-Ramirez J. Jaime Miranda Benedetta Armocida Jorge César Correia Harriette Gillian Christine Van Spall David Beran Amirali Aali Kalkidan Hassen Abate Semagn Mekonnen Abate Cristiana Abbafati Mohsen Abbasi-Kangevari Zeinab Abbasi-Kangevari Zahra Aryan Sina Azadnajafabad Mohammadreza Azangou-Khyavy Seyyed-Hadi Ghamari Mohammad Keykhaei Javad Khanali Sara Momtazmanesh Fateme Montazeri Shayan Rahmani Mohammad-Mahdi Rashidi Nazila Rezaei Negar Rezaei Sahar Saeedi Moghaddam Hossein Hassanian-Moghaddam Ali-Asghar Kolahi Ali Nikoobar Hedayat Abbastabar Ahmed M. Abdel-Azeem Michael Abdelmasseh Juan Sanabria Sherief Abd-Elsalam Ahmed Abdelwahab Gholamreza Abdoli Mohammad Abdollahi Meriem Abdoun Deldar Morad Abdulah Abu Yousuf Md Abdullah Ame Mehadi Abdurehman Getachew Abebe Aidin Abedi Chirag P. Doshi Vida Abedi Hassan Abidi Richard Gyan Aboagye Hassan Abolhassani Nima Rezaei Lucas Guimarães Abreu Michael R. M. Abrigo Yonas Derso Abtew Hiwa Abubaker Ali Eman Abu-Gharbieh Hiba Jawdat Barqawi Rabih Halwani Maha Mohamed Saber-Ayad Iman M. Talaat Ahmed Abu-Zaid Manfred Mario Kokou Accrombessi Juan Manuel Acuna Denberu Eshetie Adane Tigist Demssew Adane Isaac Yeboah Addo Giovanni Addolorato Oluwafemi Atanda Adeagbo Victor Adekanmbi Miracle Ayomikun Adesina Isaac Iyinoluwa Olufadewa Olatunji O. Adetokunboh Daniel Adedayo Adeyinka Qorinah Estiningtyas Sakilah Adnani Aanuoluwapo Adeyimika Afolabi Olayinka Stephen Ilesanmi Muhammad Sohail Afzal Saira Afzal Gina Agarwal Prerna Agarwal Pradyumna Agasthi Anurag Agrawal Marcela Agudelo-Botero Adolfo Martinez-Valle Bright Opoku Ahinkorah Aqeel Ahmad Sajjad Ahmad Sohail Ahmad Tauseef Ahmad Ali Ahmadi Siamak Sabour Keivan Ahmadi Sanjay Basu Sepideh Ahmadi Ali Ahmed Shaun Wen Huey Lee Ayman Ahmed Haroon Ahmed Jivan Qasim Ahmed Gahin Abdulraheem Tayib Yahya Yahya Luai A. Ahmed Iffat Elbarazi Syed Mahboob Shah Janardhana P. Aithala Marjan Ajami Budi Aji Hossein Akbarialiabad Yibeltal Akelew Meisam Akhlaghdoust Elham Jamshidi Addis Aklilu Azene Tesfaye Melat Woldemariam Maxwell Ak CRONICAS Center of Excellence in Chronic Diseases Universidad Peruana Cayetano Heredia Lima Peru School of Medicine Universidad Peruana Cayetano Heredia Lima Peru Sydney School of Public Health Faculty of Medicine and Health University of Sydney Sydney NSW Australia Faculty of Epidemiology and Population Health London School of Hygiene & Tropical Medicine London UK Division of Tropical and Humanitarian Medicine University of Geneva Geneva Switzerland Department of Cardiovascular Endocrine-metabolic Diseases and Aging Istituto Superiore di Sanità Rome Italy Division of Endocrinology Diabetology Nutrition and Therapeutic Patient Education Department of Medicine Geneva University Hospitals Geneva Switzerland Department of Medicine and Department of Health Research Evidence and Impact McMaster University Hamilton ON Canada Research Institute of St. Joe’s Hamilton ON Canada Population Health Research Institute Hamilton Canada Geneva University Hospitals Geneva Switzerland Faculty of Medicine Mashhad University of Medical Sciences Mashhad Iran Department of Nutrition and Dietetics Jimma University Jimma Ethiopia Anesthesiology Department Dilla University Addis Ababa Ethiopia Department of Juridical and Economic Studies La Sapienza University Rome Italy Non-Communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Brigham and Women’s Hospital Harvard University Boston MA USA Students’ Scientific Research Center (SSRC) Tehran University of Medical Sciences Tehran Iran School of Medicine Tehran University of Medical Sciences Tehran Iran School of Medicine Shahid Beheshti University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Institute Tehran University of Medical Sciences Tehran Iran Chapter of Addiction Medicine University of Sydney Sydney NSW Australia Advanced Diagnostic and Intervent

Chronic care manages long-term, progressive conditions, while acute care addresses short-term conditions. Chronic conditions increasingly strain health systems, which are often unprepared for these demands. This study examines the burden of conditions requiring acute versus chronic care, including sequelae. Conditions and sequelae from the Global Burden of Diseases Study 2019 were classified into acute or chronic care categories. Data were analysed by age, sex, and socio-demographic index, presenting total numbers and contributions to burden metrics such as Disability-Adjusted Life Years (DALYs), Years Lived with Disability (YLD), and Years of Life Lost (YLL). Approximately 68% of DALYs were attributed to chronic care, while 27% were due to acute care. Chronic care needs increased with age, representing 86% of YLDs and 71% of YLLs, and accounting for 93% of YLDs from sequelae. These findings highlight that chronic care needs far exceed acute care needs globally, necessitating health systems to adapt accordingly. © 2025. The Author(s).

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Mycorrhizal symbioses and tree diversity in global forest communities

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Science Advances 2025年第24期11卷 eadt5743页

作者： Feng Jiang Xucai Pu Bernhard Schmid Peter B. Reich Jingjing Liang Akane O. Abbasi Jesús Aguirre-Gutiérrez Angelica Maria Almeyda Zambrano Jan Altman Juan Gabriel Álvarez-González Luciana F. Alves Bienvenu H. K. Amani Christian Ammer Gerardo A. Aymard Naveen Babu Kanda Meredith L. Bastian Jean-Francois Bastin Marijn Bauters Pascal Boeckx Svetlana N. Bondarchuk Alexander Bondarev Francis Q. Brearley Sophie Brennan Jaime Briseño-Reyes Eben N. Broadbent Goran Češljar Han Y. H. Chen Chelsea Chisholm WookJin Choi Emil Cienciala Connie J. Clark Alessio Collalti José Javier Corral-Rivas Javid Ahmad Dar Selvadurai Dayanandan Sergio de-Miguel Ashaq Ahmad Dar Géraldine Derroire Ilija Djordjevic Tran Van Do Jiří Doležal Aurélie Dourdain Teresa Eyre Adandé Belarmain Fandohan Lorenzo Frizzera Roberto Cazzolla Gatti Damiano Gianelle M. Socorro González Elizondo Elisa Grieco David J. Harris Andy Hector Bruno Hérault Cang Hui Nobuo Imai Andrzej M. Jagodziński Chengjun Ji Lin Jiang Carlos A. Joly Viktor N. Karminov Kuswata Kartawinata Justin N. Kassi Elizabeth Kearsley Gunnar Keppel Mohammed Latif Khan Carine Klauberg Kirill A. Korznikov Subashree Kothandaraman Florian Kraxner Leonid Krivobokov Dmitry Kucher Amit Kumar Anna Kvashnina Gaia Vaglio Laurin Rodrigo Vieira Leite Moses B. Libalah Ekaterina S. Lonkina Huicui Lu Shan Luo Yuan Luo Emma Mackintosh Andrew R. Marshall Rodolfo Vásquez Martínez Radim Matula William McDonald Ayyappan Narayanan María Guadalupe Nava-Miranda Jagadeesan Naveenkumar Abel Monteagudo Mendoza Stanisław Miścicki Tatyana Moskalyuk Liudmila Mukhortova Sharif A. Mukul Gert-Jan Nabuurs Victor J. Neldner Radovan Nevenic Anny E. N’Guessan Michael Ngugi Alain Paquette Elena I. Parfenova Marc Parren Narayanaswamy Parthasarathy Pablo L. Peri Sebastian Pfautsch Maria T. F. Piedade Galina Polyakova Axel Dalberg Poulsen John R. Poulsen Hans Pretzsch Mirco Rodeghiero Ervan Rutishauser Purabi Saikia Philippe Saner Dmitry Schepaschenko Jochen Schöngart Eric B. Searle Douglas Sheil Zehao Shen Stephanie Shooner Anatoly Sh Institute of Ecology and State Key Laboratory for Vegetation Structure Function and Construction (VegLab) College of Urban and Environmental Sciences Peking University Beijing China. Remote Sensing Laboratories Department of Geography University of Zürich Zürich Switzerland. Department of Forest Resources University of Minnesota St Paul MN 55108 USA. Hawkesbury Institute for the Environment Western Sydney University Penrith New South Wales Australia. Institute for Global Change Biology and School for Environment and Sustainability University of Michigan Ann Arbor MI 48109 USA. Forest Advanced Computing and Artificial Intelligence Laboratory (FACAI) Department of Forestry and Natural Resources Purdue University West Lafayette IN USA. Environmental Change Institute School of Geography and the Environment University of Oxford Oxford UK. Leverhulme Centre for Nature Recovery University of Oxford Oxford UK OX13QY. Spatial Ecology and Conservation (SPEC) Lab Center for Latin American Studies University of Florida Gainesville FL 32611 USA. Institute of Botany of the Czech Academy of Sciences Třeboň Czech Republic. Faculty of Forestry and Wood Sciences Czech University of Life Sciences Prague Czech Republic. Departamento de Ingeniería Agroforestal Universidad de Santiago de Compostela Lugo Spain. Center for Tropical Research Institute of the Environment and Sustainability University of California Los Angeles Los Angeles CA 90095 USA. Université Jean Lorougnon Guédé Unité de Formation et de Recherche en Agroforesterie BP 150 Daloa Ivory Coast. Université Nangui Abrogoua Unité de Formation et de Recherche en Sciences de la Nature 02 BP 801 Abidjan 02 Laboratoire d’Écologie et du Développement durable (LEDD) Abidjian Ivory Coast. Silviculture and Forest Ecology Georg August-University of Göttingen Göttingen Germany. UNELLEZ-Guanare Programa de Ciencias del Agro y el Mar Herbario Universitario (PORT) Portuguesa Venezuela. Jardín Botánico de Bogotá José Cele

Unraveling the mechanisms underlying the maintenance of species diversity is a central pursuit in ecology. It has been hypothesized that ectomycorrhizal (EcM) in contrast to arbuscular mycorrhizal fungi can reduce tree species diversity in local communities, which remains to be tested at the global scale. To address this gap, we analyzed global forest inventory data and revealed that the relationship between tree species richness and EcM tree proportion varied along environmental gradients. Specifically, the relationship is more negative at low latitudes and in moist conditions but is unimodal at high latitudes and in arid conditions. The negative association of EcM tree proportion on species diversity at low latitudes and in humid conditions is likely due to more negative plant-soil microbial interactions in these regions. These findings extend our knowledge on the mechanisms shaping global patterns in plant species diversity from a belowground view.

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Population of Merging Compact Binaries Inferred Using Gravitational Waves through GWTC-3

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Physical Review X 2023年第1期13卷 011048-011048页

作者： R. Abbott T. D. Abbott F. Acernese K. Ackley C. Adams N. Adhikari R. X. Adhikari V. B. Adya C. Affeldt D. Agarwal M. Agathos K. Agatsuma N. Aggarwal O. D. Aguiar L. Aiello A. Ain P. Ajith T. Akutsu P. F. de Alarcón S. Akcay S. Albanesi A. Allocca P. A. Altin A. Amato C. Anand S. Anand A. Ananyeva S. B. Anderson W. G. Anderson M. Ando T. Andrade N. Andres T. Andrić S. V. Angelova S. Ansoldi J. M. Antelis S. Antier F. Antonini S. Appert Koji Arai Koya Arai Y. Arai S. Araki A. Araya M. C. Araya J. S. Areeda M. Arène N. Aritomi N. Arnaud M. Arogeti S. M. Aronson K. G. Arun H. Asada Y. Asali G. Ashton Y. Aso M. Assiduo S. M. Aston P. Astone F. Aubin C. Austin S. Babak F. Badaracco M. K. M. Bader C. Badger S. Bae Y. Bae A. M. Baer S. Bagnasco Y. Bai L. Baiotti J. Baird R. Bajpai M. Ball G. Ballardin S. W. Ballmer A. Balsamo G. Baltus S. Banagiri D. Bankar J. C. Barayoga C. Barbieri B. C. Barish D. Barker P. Barneo F. Barone B. Barr L. Barsotti M. Barsuglia D. Barta J. Bartlett M. A. Barton I. Bartos R. Bassiri A. Basti M. Bawaj J. C. Bayley A. C. Baylor M. Bazzan B. Bécsy V. M. Bedakihale M. Bejger I. Belahcene V. Benedetto D. Beniwal T. F. Bennett J. D. Bentley M. BenYaala F. Bergamin B. K. Berger S. Bernuzzi C. P. L. Berry D. Bersanetti A. Bertolini J. Betzwieser D. Beveridge R. Bhandare U. Bhardwaj D. Bhattacharjee S. Bhaumik I. A. Bilenko G. Billingsley S. Bini R. Birney O. Birnholtz S. Biscans M. Bischi S. Biscoveanu A. Bisht B. Biswas M. Bitossi M.-A. Bizouard J. K. Blackburn C. D. Blair D. G. Blair R. M. Blair F. Bobba N. Bode M. Boer G. Bogaert M. Boldrini L. D. Bonavena F. Bondu E. Bonilla R. Bonnand P. Booker B. A. Boom R. Bork V. Boschi N. Bose S. Bose V. Bossilkov V. Boudart Y. Bouffanais A. Bozzi C. Bradaschia P. R. Brady A. Bramley A. Branch M. Branchesi J. Brandt J. E. Brau M. Breschi T. Briant J. H. Briggs A. Brillet M. Brinkmann P. Brockill A. F. Brooks J. Brooks D. D. Brown S. Brunett G. Bruno R. Bruntz J. Bryant T. Bulik H. J. Bulten A. Buonanno R. Buscicchio D. Buskulic C. Buy R. L. Byer L. Cadonati LIGO Laboratory California Institute of Technology Pasadena California 91125 USA Louisiana State University Baton Rouge Louisiana 70803 USA Dipartimento di Farmacia Università di Salerno I-84084 Fisciano Salerno Italy INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo I-80126 Napoli Italy OzGrav School of Physics & Astronomy Monash University Clayton 3800 Victoria Australia LIGO Livingston Observatory Livingston Louisiana 70754 USA University of Wisconsin-Milwaukee Milwaukee Wisconsin 53201 USA OzGrav Australian National University Canberra Australian Capital Territory 0200 Australia Max Planck Institute for Gravitational Physics (Albert Einstein Institute) D-30167 Hannover Germany Leibniz Universität Hannover D-30167 Hannover Germany Inter-University Centre for Astronomy and Astrophysics Pune 411007 India University of Cambridge Cambridge CB2 1TN United Kingdom Theoretisch-Physikalisches Institut Friedrich-Schiller-Universität Jena D-07743 Jena Germany University of Birmingham Birmingham B15 2TT United Kingdom Center for Interdisciplinary Exploration & Research in Astrophysics (CIERA) Northwestern University Evanston Illinois 60208 USA Instituto Nacional de Pesquisas Espaciais 12227-010 São José dos Campos São Paulo Brazil Gravity Exploration Institute Cardiff University Cardiff CF24 3AA United Kingdom INFN Sezione di Pisa I-56127 Pisa Italy International Centre for Theoretical Sciences Tata Institute of Fundamental Research Bengaluru 560089 India Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Universitat de les Illes Balears IAC3–IEEC E-07122 Palma de Mallorca Spain University College Dublin Dublin 4 Ireland INFN Sezione di Torino I-10125 Torino Italy Università di Napoli “Federico II” Complesso Universitario di Monte S. Angelo I-80126 Napoli

We report on the population properties of compact binary mergers inferred from gravitational-wave observations of these systems during the first three LIGO-Virgo observing runs. The Gravitational-Wave Transient Catalog 3 (GWTC-3) contains signals consistent with three classes of binary mergers: binary black hole, binary neutron star, and neutron star–black hole mergers. We infer the binary neutron star merger rate to be between 10 and 1700 Gpc−3 yr−1 and the neutron star–black hole merger rate to be between 7.8 and 140 Gpc−3 yr−1, assuming a constant rate density in the comoving frame and taking the union of 90% credible intervals for methods used in this work. We infer the binary black hole merger rate, allowing for evolution with redshift, to be between 17.9 and 44 Gpc−3 yr−1 at a fiducial redshift (z=0.2). The rate of binary black hole mergers is observed to increase with redshift at a rate proportional to (1+z)κ with κ=2.9−1.8+1.7 for z≲1. Using both binary neutron star and neutron star–black hole binaries, we obtain a broad, relatively flat neutron star mass distribution extending from 1.2−0.2+0.1 to 2.0−0.3+0.3M⊙. We confidently determine that the merger rate as a function of mass sharply declines after the expected maximum neutron star mass, but cannot yet confirm or rule out the existence of a lower mass gap between neutron stars and black holes. We also find the binary black hole mass distribution has localized over- and underdensities relative to a power-law distribution, with peaks emerging at chirp masses of 8.3−0.5+0.3 and 27.9−1.8+1.9M⊙. While we continue to find that the mass distribution of a binary’s more massive component strongly decreases as a function of primary mass, we observe no evidence of a strongly suppressed merger rate above approximately 60M⊙, which would indicate the presence of a upper mass gap. Observed black hole spins are small, with half of spin magnitudes below χi≈0.25. While the majority of spins are preferentially aligned wi

关键词： Gravitational wave sources Gravitational waves Gravitational wave detection

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